Scoring upper-extremity motor function from EEG with artificial neural networks: a preliminary study.

Journal: Journal of neural engineering
Published Date:

Abstract

OBJECTIVE: Motor function of chronic stroke survivors is generally accessed using clinical motor assessments. These motor assessments are partially subjective and require prior training for the examiners. Additionally, those motor function assessments require the health professionals to be present in person. The method proposed in this paper has the potential to radically change the way motor function is assessed.

Authors

  • Xin Zhang
    First Department of Infectious Diseases, The First Affiliated Hospital of China Medical University, Shenyang, China.
  • Ryan D'Arcy
  • Carlo Menon
    Menrva Research Group, Schools of Mechatronic Systems & Engineering Science at Simon Fraser University (SFU), Burnaby, BC V5A 1S6, Canada. cmenon@sfu.ca.